Promoting Bifunctional Oxygen Catalyst Activity of Double-Perovskite-Type Cubic Nanocrystallites for Aqueous and Quasi-Solid-State Rechargeable Zinc-Air Batteries

Transition metal oxide materials are promising oxygen catalysts that are alternatives to expensive and precious metal-containing catalysts. Integration of transition metal oxides with high activity for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is an important pathway for good bifunctionality. In contrast to the conventional physical mixing and hybridization strategies, perovskite-type oxide provides an ideal structure for the integration of the transition metal element atoms on an atomic scale. Herein, B-site ordered double-perovskite-type La1.6Sr0.4MnCoO6 nanocrystallites with ultra-small cubic (20–50 nm) morphology and high specific surface areas (25 m2 g−1) were proposed. Rational designs were integrated to promote the ORR-OER catalysis, e.g., introducing oxygen vacancies via A-site cation substitution, further increasing surface oxygen vacancies via integration of a small amount of Pt/C and nanosizing of the material via a facile molten-salt method. The batteries with the La1.6Sr0.4MnCoO6 nanocrystallites and an aqueous alkaline electrolyte demonstrate decent discharge−charge voltage gaps of 0.75 and 1.10 V at 1 and 30 mA cm−2, respectively, and good cycling stability of 250 h (1500 cycles). A coin-type battery with a gel−polymer electrolyte also presents a good performance

Nanoporous Structure of Sintered Metal Powder Heat Exchanger in Dilution Refrigeration: A Numerical Study

We use LAMMPS to randomly pack hard spheres to simulate the heat exchanger, where the hard spheres represent sintered metal particles in the heat exchanger. We simulated the heat exchanger under different sphere radii and different packing fractions of the metal particle and researched pore space. To improve the performance of the heat exchanger, we adopted this simulation method to explore when the packing fraction is 65%, the optimal sintering particle radius in the heat exchanger is 30~35nm.Comment: 5 pages,3 figures, one tabl

Endocrine disrupting chemical Bisphenol A and its association with cancer mortality: a prospective cohort study of NHANES

IntroductionThere is evidence suggesting that Bisphenol A (BPA) is associated with increased all-cause mortality in adults. However, the specific nature of the relationship between BPA exposure and cancer mortality remains relatively unexplored.MethodsThe National Health and Nutrition Examination Survey (NHANES) dataset was used to recruit participants. Urinary BPA was assessed using liquid chromatography-mass spectrum (LC–MS). Through the use of multivariable Cox proportional hazard regressions and constrained cubic splines, the relationships between urine BPA and death from all causes and cancer were investigated.ResultsThis study has a total of 8,035 participants, and 137 died from cancers after a 7.5-year follow-up. The median level of BPA was 2.0 g/mL. Urinary BPA levels were not independently associated with all-cause mortality. For cancer mortality, the second quartile’s multivariable-adjusted hazard ratio was 0.51 (95% confidence interval: 0.30 to 0.86; p = 0.011) compared to the lowest quartile. The restricted cubic splines showed that the association was nonlinear (p for nonlinearity = 0.028) and the inflection point was 1.99 ng/mL.ConclusionUrinary BPA exposure was U-shaped associated with the risk of cancer mortality, and a lower level of BPA less than 1.99 ng/mL was associated with a higher risk of cancer mortality

Map-based Channel Modeling and Generation for U2V mmWave Communication

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including interpath and intra-path are analyzed in detail. The inter-path parameters are calculated in a deterministic way, while the parameters of intra-path rays are generated in a stochastic way. The statistical properties are obtained by using a Gaussian mixture model (GMM) on the massive ray tracing (RT) data. Then, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. Meanwhile, to reduce the complexity of RT method, the 3D propagation space is reconstructed based on the user-defined digital map. The simulated and analyzed results show that the proposed model and generation method can reproduce non-stationary U2V channels in accord with U2V scenarios. The generated statistical properties are consistent with the theoretical and measured ones as well

A porous nano-micro-composite as a high-performance bi-functional air electrode with remarkable stability for rechargeable zinc–air batteries

The development of bi-functional electrocatalyst with high catalytic activity and stable performance for both oxygen evolution/reduction reactions (OER/ORR) in aqueous alkaline solution is key to realize practical application of zinc–air batteries (ZABs). In this study, we reported a new porous nano-micro-composite as a bi-functional electrocatalyst for ZABs, devised by the in situ growth of metal–organic framework (MOF) nanocrystals onto the micrometer-sized Ba0.5Sr0.5Co0.8Fe0.2O3 (BSCF) perovskite oxide. Upon carbonization, MOF was converted to porous nitrogen-doped carbon nanocages and ultrafine cobalt oxides and CoN4 nanoparticles dispersing inside the carbon nanocages, which further anchored on the surface of BSCF oxide. We homogeneously dispersed BSCF perovskite particles in the surfactant; subsequently, ZIF-67 nanocrystals were grown onto the BSCF particles. In this way, leaching of metallic or organic species in MOFs and the aggregation of BSCF were effectively suppressed, thus maximizing the number of active sites for improving OER. The BSCF in turn acted as catalyst to promote the graphitization of carbon during pyrolysis, as well as to optimize the transition metal-to-carbon ratio, thus enhancing the ORR catalytic activity. A ZAB fabricated from such air electrode showed outstanding performance with a potential gap of only 0.83 V at 5 mA cm−2 for OER/ORR. Notably, no obvious performance degradation was observed for the continuous charge–discharge operation for 1800 cycles over an extended period of 300 h

Building a digital twin of EDFA: a grey-box modeling approach

To enable intelligent and self-driving optical networks, high-accuracy physical layer models are required. The dynamic wavelength-dependent gain effects of non-constant-pump erbium-doped fiber amplifiers (EDFAs) remain a crucial problem in terms of modeling, as it determines optical-to-signal noise ratio as well as the magnitude of fiber nonlinearities. Black-box data-driven models have been widely studied, but it requires a large size of data for training and suffers from poor generalizability. In this paper, we derive the gain spectra of EDFAs as a simple univariable linear function, and then based on it we propose a grey-box EDFA gain modeling scheme. Experimental results show that for both automatic gain control (AGC) and automatic power control (APC) EDFAs, our model built with 8 data samples can achieve better performance than the neural network (NN) based model built with 900 data samples, which means the required data size for modeling can be reduced by at least two orders of magnitude. Moreover, in the experiment the proposed model demonstrates superior generalizability to unseen scenarios since it is based on the underlying physics of EDFAs. The results indicate that building a customized digital twin of each EDFA in optical networks become feasible, which is essential especially for next generation multi-band network operations

Attitudes of Chinese maternal and child health professionals toward termination of pregnancy for fetal anomaly: a cross-sectional survey

ObjectivesThis study explores the attitudes of Chinese maternal and child health professionals toward the termination of pregnancy for fetal anomaly (TOPFA) based on four case scenarios and further identifies the factors that influence their attitudes.MethodsThis cross-sectional study, conducted from February 14–21, 2022, aimed to explore the attitudes of maternal and child health professionals toward TOPFA in Hunan Province. We targeted health service institutions across 14 prefecture-level cities and the autonomous prefecture. A questionnaire was made available online and shared via the instant communication platform, WeChat. Participants were recruited through the same platform and completed the survey online. Descriptive statistics were used to analyze the data, and binary logistic regression was performed to determine factors affecting the health professionals’ attitudes toward TOPFA, expressed as the odds ratio (OR) and 95% confidence intervals (CI).ResultsThe study found that 63.5% of health professionals approved of the birth of a fetus with cleft lip and palate, while 36.5% opposed it. Similarly, 39.7% approved of the birth of a fetus with phenylketonuria, while 60.3% opposed it. The percentages of those in favor of and against the birth of a fetus with precocious heart disease were 45.5 and 54.5%, respectively, and those for and against the birth of a fetus with missing fingers were 50.8 and 49.2%, respectively. The top three factors considered by health professionals when agreeing on TOPFA were “the impact of fetal disease on fetal function and growth,” “the severity of fetal disease,” and “the assessment of indications for fetal disease by professionals and related professional advice.” The majority of health professionals (75–78%) preferred joint decision-making by parents regarding the right to decide TOPFA.ConclusionOur study indicates that the attitudes of health professionals toward TOPFA can differ significantly depending on the specific birth defect under consideration. Notably, the majority of health professionals prioritized “the impact of fetal abnormalities on fetal function and development” when deciding their support for TOPFA, advocating for the decision to be a joint one between the parents. Additionally, factors such as religious beliefs, professional training, age, and job title appeared to influence these attitudes toward TOPFA. Our findings could serve as a reference point in the development of guidelines for the prevention and management of birth defects

Risk of emergency hospital admission related to adverse events after antibiotic treatment in adults with a common infection: impact of COVID-19 and derivation and validation of risk prediction models

Background: With the global challenge of antimicrobial resistance intensified during the COVID-19 pandemic, evaluating adverse events (AEs) post-antibiotic treatment for common infections is crucial. This study aims to examines the changes in incidence rates of AEs during the COVID-19 pandemic and predict AE risk following antibiotic prescriptions for common infections, considering their previous antibiotic exposure and other long-term clinical conditions. Methods: With the approval of NHS England, we used OpenSAFELY platform and analysed electronic health records from patients aged 18–110, prescribed antibiotics for urinary tract infection (UTI), lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), sinusitis, otitis externa, and otitis media between January 2019 and June 2023. We evaluated the temporal trends in the incidence rate of AEs for each infection, analysing monthly changes over time. The survival probability of emergency AE hospitalisation was estimated in each COVID-19 period (period 1: 1 January 2019 to 25 March 2020, period 2: 26 March 2020 to 8 March 2021, period 3: 9 March 2021 to 30 June 2023) using the Kaplan–Meier approach. Prognostic models, using Cox proportional hazards regression, were developed and validated to predict AE risk within 30 days post-prescription using the records in Period 1. Results: Out of 9.4 million patients who received antibiotics, 0.6% of UTI, 0.3% of URTI, and 0.5% of LRTI patients experienced AEs. UTI and LRTI patients demonstrated a higher risk of AEs, with a noted increase in AE incidence during the COVID-19 pandemic. Higher comorbidity and recent antibiotic use emerged as significant AE predictors. The developed models exhibited good calibration and discrimination, especially for UTIs and LRTIs, with a C-statistic above 0.70. Conclusions: The study reveals a variable incidence of AEs post-antibiotic treatment for common infections, with UTI and LRTI patients facing higher risks. AE risks varied between infections and COVID-19 periods. These findings underscore the necessity for cautious antibiotic prescribing and call for further exploration into the intricate dynamics between antibiotic use, AEs, and the pandemic